Effect of film thickness on hydrogen content in a-Si : H

The hydrogen content, its depth distribution, and its bonding configuration have been studied in hydrogenated amorphous silicon prepared by plasma-enhanced chemical vapor deposition with hydrogen-diluted silane. Nuclear reaction analysis and infrared spectroscopy were used to determine the total amount of hydrogen and its bonded component, respectively. It has been established that the total concentration of hydrogen does not depend on the film thickness, and has a uniform depth profile. The concentration of bonded hydrogen changes with the film thickness within the measurement accuracy. The data obtained suggest the presence of molecular (non-bonded) hydrogen, uniformly distributed in concentration across the film thickness.     

Lateral ion implant straggle and mask proximity effect

Lateral scattering of retrograde well implants is shown to have an effect on the threshold voltage of nearby devices. The threshold voltage of both NMOSFETs and PMOSFETs increases in magnitude for conventional retrograde wells, but for triple-well isolated NMOSFETs the threshold voltage decreases for narrow devices near the edge of the well. Electrical data, SIMS, and SUPREM4 simulations are shown that elucidate the phenomenon.     

Operating Penalties in Single-Fiber Operation 10-Gb/s, 1024-Way Split, 110-km Long-Reach Optical Access Networks

We report for the first time optical signal-to-noise penalties which lead to performance degradations in single-fiber long-reach optical access networks when compared to identical dual-fiber systems. A simplified architecture, with reduced optical amplifier count compared to previous work, for single-fiber operation of a symmetrical 10-Gb/s, 1024-way split, 110-km long-reach optical access network is presented and demonstrated. In addition, a possible solution to remove the optical signal-to-noise penalty is suggested     

A decision support system for interactive decision making - Part II: analysis and output interpretation

For pt.I see ibid., p.42-55 (2003). The development of a comprehensive decision support system, GMCR II, for the systematic study of real-world interactive decision problems is presented. The companion paper (Part I), discusses how GMCR II elicits, stores, and manages conflict models; here (Part II), the focus is on GMCR IIs analysis and output interpretation subsystems. Specifically, this paper describes the powerful and efficient analysis engine contained in GMCR II, its informative output presentation and interpretation facilities, and a number of follow-up analyses. Furthermore, an illustrative case study is used to demonstrate how GMCR II can be conveniently applied in practice.     

Mass Transfer in a Flat Gas/Liquid Interface using non‐Newtonian Media

Gas/liquid mass transfer has been investigated using a stirred vessel gas/liquid contactor using non‐Newtonian media and carbon dioxide as absorbent and gas phase, respectively. The volumetric mass transfer coefficients at different operational variables have been determined. Non‐Newtonian media (liquid phase) were prepared as aqueous solutions of sodium carboxymethyl cellulose salt. The influence of the rheological properties, polymer concentration, stirring rate, and gas flow rate on mass transfer was studied for these liquid phases. Kinematic viscosity and density experimental data were used to calculate the average molecular weight corresponding to the polymer employed. The Ostwald model has been used to fit the rheological behavior of aqueous solutions of the polymer employed as absorbent phase. Reasonably good agreement was found between the predictions of the proposed models and the experimental data of mass transfer coefficients.     

Asymptotic performance of single parity-check product codes

This article investigates the asymptotic performance of single parity-check (SPC) product codes (PCs) from a decoding point of view. Specifically, the probability of bit error is bounded before and after the decoding of each dimension, similar to the analysis of "iterated codes" by Elias (1954). It is shown that the asymptotic probability of bit error can be driven to zero as the number of dimensions, and hence the block length, increases at signal-to-noise ratios (SNRs) within 2 dB of capacity over the additive white Gaussian noise (AWGN) channel.     

High-efficiency LEDs of 1.6–2.4 µm spectral range for medical diagnostics and environment monitoring

High efficient LED structures covering the spectral range of 1.6–2.4 μm have been developed on the basis of GaSb and its solid solutions. The electroluminescent characteristics and their temperature and current dependences have been studied. The radiative and nonradiative recombination mechanisms and their effect on the quantum efficiency have been investigated. A quantum efficiency of 40–60% has been obtained in the quasi-steady mode at room temperature. A short-pulse optical power of 170 mW was reached. __________ Translated from Fizika i Tekhnika Poluprovodnikov, Vol. 37, No. 8, 2003, pp. 996–1009. Original Russian Text Copyright ? 2003 by Stoyanov, Zhurtanov, Astakhova, Imenkov, Yakovlev.     

A fuzzy logic based-method for prognostic decision making in breast and prostate cancers

Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than both the statistical and artificial neural-network-based methods.